FinTech and Inclusive Green Growth: A Causal Inference Based on Double Machine Learning

Binhong Wu, Yuting Ding, Bangsheng Xie () and Yu Zhang ()
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Binhong Wu: School of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China
Yuting Ding: School of Economics and Management, Fujian Agriculture and Forestry University, Fuzhou 350002, China
Bangsheng Xie: School of Economics and Management, Fujian Agriculture and Forestry University, Fuzhou 350002, China
Yu Zhang: School of Economics and Management, Fujian Agriculture and Forestry University, Fuzhou 350002, China

Sustainability, 2024, vol. 16, issue 22, 1-24

Abstract: Based on city-level data from 287 Chinese prefecture-level administrative units spanning 2011 to 2021, this study employs text analysis to quantify FinTech development and applies a double machine learning model to empirically assess the impact of FinTech on Inclusive Green Growth, along with its underlying mechanisms. The key findings are as follows: (1) FinTech significantly promotes Inclusive Green Growth, particularly in the areas of payment systems, lending and capital raising, and investment management. This conclusion holds across a range of robustness checks, including alternative measurement indicators, different machine learning models, and tests for endogeneity. (2) Mechanism analysis demonstrates that FinTech drives Inclusive Green Growth by fostering financial employment, expanding financial supply, and facilitating green technological innovation. (3) Heterogeneity analysis reveals that while China still faces elements of the resource curse, the positive impact of FinTech on Inclusive Green Growth is more pronounced in regions with higher levels of digital infrastructure, environmental regulation, and green finance. These findings provide valuable insights into leveraging FinTech’s potential to support China’s high-quality economic development.

Keywords: FinTech; Inclusive Green Growth; double machine learning (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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